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Many developing countries consider financial institutions that are locally incorporated or even state-owned monopolies an essential element of their economic and political independence. This cross-sectional study of developing countries presents some empirical tests of the relationship between financial development and the development of the life insurance sector and provides empirical evidence of the negative effect of a monopolistic market on life insurance growth.
Insurance market activity, both as a financial intermediary and a provider of risk transfer and indemnification, may contribute to economic growth by allowing different risks to be managed more efficiently and by mobilizing domestic savings. During the past decade, there has been faster growth in insurance market activity, particularly in emerging markets given the process of liberalization and financial integration, which raises questions about its impact on economic growth. The author tests whether there is a causal relationship between insurance market activity (life and nonlife insurance) and economic growth. Using the generalized method of moments for dynamic models of panel data for 56 countries and for the 1976-2004 period, he finds robust evidence of a causal relationship between insurance market activity and economic growth. Both life and nonlife insurance have a positive and significant causal effect on economic growth. High-income countries drive the results in the case of life insurance. On the other hand, both high-income and developing countries drive the results in the case of nonlife insurance.
Specialist groups have often advised health ministers and other decision makers in developing countries on the use of social health insurance (SHI) as a way of mobilizing revenue for health, reforming health sector performance, and providing universal coverage. This book reviews the specific design and implementation challenges facing SHI in low- and middle-income countries and presents case studies on Ghana, Kenya, Philippines, Colombia, and Thailand.
This volume describes the evolution of the social security approach to health insurance, from the first initiatives in Europe to the adaptation of the concept in other parts of the world. It then focuses on benefits and financing, and on the inter-relationship between the social security system and government agencies, particularly those dealing with health.; A concise review of the mechanisms involved in both the delivery of health services and providing payment is followed by an analysis of current administrative issues. The second part contains country profiles of health care programmes in.
Over the past twenty years, many low- and middle-income countries have experimented with health insurance options. While their plans have varied widely in scale and ambition, their goals are the same: to make health services more affordable through the use of public subsidies while also moving care providers partially or fully into competitive markets. Until now, however, we have known little about the actual effects of these dramatic policy changes. Understanding the impact of health insurance-based care is key to the public policy debate of whether to extend insurance to low-income populationsand if so, how to do itor to serve them through other means.
Insurance market activity, both as a financial intermediary and a provider of risk transfer and indemnification, may contribute to economic growth by allowing different risks to be managed more efficiently and by mobilizing domestic savings. During the past decade, there has been faster growth in insurance market activity, particularly in emerging markets given the process of liberalization and financial integration, which raises questions about its impact on economic growth. The author tests whether there is a causal relationship between insurance market activity (life and nonlife insurance) and economic growth. Using the generalized method of moments for dynamic models of panel data for 56 countries and for the 1976-2004 period, he finds robust evidence of a causal relationship between insurance market activity and economic growth. Both life and nonlife insurance have a positive and significant causal effect on economic growth. High-income countries drive the results in the case of life insurance. On the other hand, both high-income and developing countries drive the results in the case of nonlife insurance.
During the last 25 years, life expectancy at age 50 in the United States has been rising, but at a slower pace than in many other high-income countries, such as Japan and Australia. This difference is particularly notable given that the United States spends more on health care than any other nation. Concerned about this divergence, the National Institute on Aging asked the National Research Council to examine evidence on its possible causes. According to Explaining Divergent Levels of Longevity in High-Income Countries, the nation's history of heavy smoking is a major reason why lifespans in the United States fall short of those in many other high-income nations. Evidence suggests that current obesity levels play a substantial part as well. The book reports that lack of universal access to health care in the U.S. also has increased mortality and reduced life expectancy, though this is a less significant factor for those over age 65 because of Medicare access. For the main causes of death at older ages-cancer and cardiovascular disease-available indicators do not suggest that the U.S. health care system is failing to prevent deaths that would be averted elsewhere. In fact, cancer detection and survival appear to be better in the U.S. than in most other high-income nations, and survival rates following a heart attack also are favorable. Explaining Divergent Levels of Longevity in High-Income Countries identifies many gaps in research. For instance, while lung cancer deaths are a reliable marker of the damage from smoking, no clear-cut marker exists for obesity, physical inactivity, social integration, or other risks considered in this book. Moreover, evaluation of these risk factors is based on observational studies, which-unlike randomized controlled trials-are subject to many biases.